142 lines
3.3 KiB
Plaintext
142 lines
3.3 KiB
Plaintext
[role="xpack"]
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[testenv="platinum"]
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[[explain-dfanalytics]]
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=== Explain {dfanalytics} API
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[subs="attributes"]
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++++
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<titleabbrev>Explain {dfanalytics} API</titleabbrev>
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++++
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Explains a {dataframe-analytics-config}.
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experimental[]
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[[ml-explain-dfanalytics-request]]
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==== {api-request-title}
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`GET _ml/data_frame/analytics/_explain` +
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`POST _ml/data_frame/analytics/_explain` +
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`GET _ml/data_frame/analytics/<data_frame_analytics_id>/_explain` +
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`POST _ml/data_frame/analytics/<data_frame_analytics_id>/_explain`
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[[ml-explain-dfanalytics-prereq]]
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==== {api-prereq-title}
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* You must have `monitor_ml` privilege to use this API. For more
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information, see <<security-privileges>> and <<built-in-roles>>.
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[[ml-explain-dfanalytics-desc]]
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==== {api-description-title}
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This API provides explanations for a {dataframe-analytics-config} that either
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exists already or one that has not been created yet.
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The following explanations are provided:
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* which fields are included or not in the analysis and why,
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* how much memory is estimated to be required. The estimate can be used when
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deciding the appropriate value for `model_memory_limit` setting later on,
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about either an existing {dfanalytics-job} or one that has not been created yet.
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[[ml-explain-dfanalytics-path-params]]
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==== {api-path-parms-title}
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`<data_frame_analytics_id>`::
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(Optional, string)
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include::{docdir}/ml/ml-shared.asciidoc[tag=job-id-data-frame-analytics]
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[[ml-explain-dfanalytics-request-body]]
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==== {api-request-body-title}
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`data_frame_analytics_config`::
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(Optional, object) Intended configuration of {dfanalytics-job}. Note that `id`
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and `dest` don't need to be provided in the context of this API.
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[[ml-explain-dfanalytics-results]]
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==== {api-response-body-title}
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The API returns a response that contains the following:
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`field_selection`::
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(array)
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include::{docdir}/ml/ml-shared.asciidoc[tag=field-selection]
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`memory_estimation`::
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(object)
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include::{docdir}/ml/ml-shared.asciidoc[tag=memory-estimation]
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[[ml-explain-dfanalytics-example]]
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==== {api-examples-title}
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[source,console]
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--------------------------------------------------
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POST _ml/data_frame/analytics/_explain
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{
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"data_frame_analytics_config": {
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"source": {
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"index": "houses_sold_last_10_yrs"
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},
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"analysis": {
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"regression": {
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"dependent_variable": "price"
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}
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}
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}
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}
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--------------------------------------------------
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// TEST[skip:TBD]
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The API returns the following results:
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[source,console-result]
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----
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{
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"field_selection": [
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{
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"field": "number_of_bedrooms",
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"mappings_types": ["integer"],
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"is_included": true,
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"is_required": false,
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"feature_type": "numerical"
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},
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{
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"field": "postcode",
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"mappings_types": ["text"],
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"is_included": false,
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"is_required": false,
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"reason": "[postcode.keyword] is preferred because it is aggregatable"
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},
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{
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"field": "postcode.keyword",
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"mappings_types": ["keyword"],
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"is_included": true,
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"is_required": false,
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"feature_type": "categorical"
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},
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{
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"field": "price",
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"mappings_types": ["float"],
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"is_included": true,
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"is_required": true,
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"feature_type": "numerical"
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}
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],
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"memory_estimation": {
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"expected_memory_without_disk": "128MB",
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"expected_memory_with_disk": "32MB"
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}
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}
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----
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